Adaptive Fuzzy Logic Control for Grinding Process Based on Grinding Sound Trend. Issue 21 (2022)

• Record Type: Journal Article
• Authors: Zou, Meiyin; Yi, Jie; Yang, Chunhua; Liao, Qian; Xiong, Wei; Wang, Xiaoli
• Is Part Of: IFAC-PapersOnLine. Volume 55:Issue 21(2022)
• Page Start: 120
• Page End: 125
• Publication Date: 2022
• Subjects: Grinding sound trend -- QTA -- Grinding optimization -- Adaptive fuzzy logic control -- FCM; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2022.09.254
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: Advanced control is significant to improve the process performance for grinding and classification process. Due to frequent variation of ore property, many advanced control methods cannot work effectively in a long period. To overcome this problem, an adaptive fuzzy logic control method based on the trend of grinding sound is proposed for grinding process. In this method, the trend of grinding sound is extracted by qualitative trend analysis (QTA), grinding sound signal and mill power are used as controller inputs to control ore feed and water feed, and improved fuzzy C-means (FCM) is adopted to adapt parameters of fuzzy controller according to actual process conditions. Simulation results show that this proposed approach achieves less fluctuation of ore feed than manual control, ensures that ore throughput meets the target of this concentrator and reduces energy consumption of ball mill.